1. Field of the Invention
The present invention generally relates to video processing, and more particularly, to a video processing method for reducing temporal noise of video images and apparatus thereof.
2. Description of the Prior Art
Noise processing along a time axis is a common form of image processing for reducing temporal noise of video images. Please refer to FIG. 1, FIG. 1 illustrates a typical temporal noise filtering module 100. The noise filtering module 100 includes a motion detector 110, a controller 120, and a temporal noise filter 130. The motion detector 110 receives an image signal S_P, which comprises a plurality of video frames, wherein the frames include at least a target frame FN to be processed and a frame FN−1 prior in time to the target frame FN. The motion detector 110 detects motion between the target frame FN and the previous frame FN−1, and outputs an image motion determination value M to the controller 120. The controller 120 then outputs a filter factor W to the temporal noise filter 130 according to the image motion determination value M. The conventional temporal noise filtering mechanism generally adopts a predetermined threshold value for the controller 120, and determines that there is motion between the frame FN and FN−1 if the image motion determination value M exceeds the predetermined threshold value. At this time, the filter factor W outputted by the controller 120 indicates that the temporal noise filter 130 will not perform filtering upon the target frame FN. Conversely, it is determined that there is no motion between the frame FN and FN−1, or the image is static, if the image motion determination value M is less than the threshold value. In this case the temporal noise filter 130 will perform filtering on the target frame FN according to the filter factor W from the controller 120, and outputs a filtered signal S_NR. Generally the conventional filtering method merely averages the pixel values of the same pixel respectively in the two frames, and then replaces the original value in the target frame FN with the average pixel value.
However, it seems crude to determine when to perform temporal noise reduction according simply to the degree of motion of the images, as described above. Additionally, the filtering method also appears overly simplified. Therefore, such a temporal noise reduction process may not be as accurate or effective as desired. Moreover, in order to minimize costs on hardware or required computational resources, conventional noise reducing or other image enhancement apparatuses reference only a single channel of the images, for example, only one of the RGB channels or one of the YUV channels when performing above-mentioned determination. The determination result referencing information from only a single channel is then used for controlling the filtering operation of the referenced channel as well as other channels. For example, the image motion determination result of the Y channel is used for controlling the filtering operation of all three of the Y, U, and V channels. As a result, because some of the channels are inadequately filtered due to referencing information not from their own channels, image quality degrades.